@article {4114,
title = {Optimal referencing for stereo-electroencephalographic (SEEG) recordings},
journal = {NeuroImage},
volume = {183},
year = {2018},
month = {12/2018},
pages = {327-335},
abstract = {Stereo-electroencephalography (SEEG) is an intracranial recording technique in which depth electrodes are inserted in the brain as part of presurgical assessments for invasive brain surgery. SEEG recordings can tap into neural signals across the entire brain and thereby sample both cortical and subcortical sites. However, even though signal referencing is important for proper assessment of SEEG signals, no previous study has comprehensively evaluated the optimal referencing method for SEEG. In our study, we recorded SEEG data from 15 human subjects during a motor task, referencing them against the average of two white matter contacts (monopolar reference). We then subjected these signals to 5 different re-referencing approaches: common average reference (CAR), gray-white matter reference (GWR), electrode shaft reference (ESR), bipolar reference, and Laplacian reference. The results from three different signal quality metrics suggest the use of the Laplacian re-reference for study of local population-level activity and low-frequency oscillatory activity.},
keywords = {Noise subtraction, Referencing method, SEEG, Signal quality, Stereo-electroencephalography},
issn = {1053-8119},
doi = {10.1016/j.neuroimage.2018.08.020},
url = {https://www.sciencedirect.com/science/article/pii/S1053811918307183},
author = {Li, G and Jiang, S and Paraskevopoulou, S and Wang, M and Xu, Y and Wu, Z and Chen, L and Zhang, D and Schalk, Gerwin}
}